diff --git a/test/test_mps.py b/test/test_mps.py
index 2a5c2d0..ddddb8a 100644
--- a/test/test_mps.py
+++ b/test/test_mps.py
@@ -2961,104 +2961,48 @@
         helper((9, 5, 6, 7))
 
     # Test var
-    def test_var(self):
-        def helper(shape):
+    def test_var_simple(self):
+        def helper():
+
+            shape = [2, 3, 4, 5]
+
             cpu_x = torch.randn(shape, device='cpu', dtype=torch.float, requires_grad=False)
             x = cpu_x.detach().clone().to('mps')
 
-            all_var = torch.var(x, unbiased=False)
-            all_var_cpu = torch.var(cpu_x, unbiased=False)
+            for unbiased in [False, True]:
+                for keepdim in [False, True]:
 
-            self.assertEqual(all_var, all_var_cpu)
+                    zero_dim_var = x.var(-1, keepdim=keepdim, unbiased=unbiased)
+                    zero_dim_var_cpu = cpu_x.var(-1, keepdim=keepdim, unbiased=unbiased)
 
-            nil_dim_var = torch.var(x, dim=[], unbiased=False)
-            nil_dim_var_cpu = torch.var(cpu_x, dim=[], unbiased=False)
+                    self.assertEqual(zero_dim_var, zero_dim_var_cpu)
 
-            self.assertEqual(nil_dim_var, nil_dim_var_cpu)
+                    all_var = torch.var(x, unbiased=unbiased)
+                    all_var_cpu = torch.var(cpu_x, unbiased=unbiased)
 
-            nil_dim_var_keepdim = torch.var(x, dim=[], keepdim=True, unbiased=False)
-            nil_dim_var_cpu_keepdim = torch.var(cpu_x, dim=[], keepdim=True, unbiased=False)
+                    self.assertEqual(all_var, all_var_cpu)
 
-            self.assertEqual(nil_dim_var_keepdim, nil_dim_var_cpu_keepdim)
+                    nil_dim_var = torch.var(x, dim=[], keepdim=keepdim, unbiased=unbiased)
+                    nil_dim_var_cpu = torch.var(cpu_x, dim=[], keepdim=keepdim, unbiased=unbiased)
 
-            zero_dim_var = torch.var(x, dim=[0], unbiased=False)
-            zero_dim_var_cpu = torch.var(cpu_x, dim=[0], unbiased=False)
+                    self.assertEqual(nil_dim_var, nil_dim_var_cpu)
 
-            self.assertEqual(zero_dim_var, zero_dim_var_cpu)
+                    zero_dim_var = torch.var(x, dim=[0], keepdim=keepdim, unbiased=unbiased)
+                    zero_dim_var_cpu = torch.var(cpu_x, dim=[0], keepdim=keepdim, unbiased=unbiased)
 
-            zero_dim_var_keepdim = torch.var(x, dim=[0], keepdim=True, unbiased=False)
-            zero_dim_var_cpu_keepdim = torch.var(cpu_x, dim=[0], keepdim=True, unbiased=False)
+                    self.assertEqual(zero_dim_var, zero_dim_var_cpu)
 
-            self.assertEqual(zero_dim_var_keepdim, zero_dim_var_cpu_keepdim)
+                    zero_one_dim_var = torch.var(x, dim=[0, -1], keepdim=keepdim, unbiased=unbiased)
+                    zero_one_dim_var_cpu = torch.var(cpu_x, dim=[0, -1], keepdim=keepdim, unbiased=unbiased)
 
-            zero_one_dim_var = torch.var(x, dim=[0, 1], unbiased=False)
-            zero_one_dim_var_cpu = torch.var(cpu_x, dim=[0, 1], unbiased=False)
+                    self.assertEqual(zero_one_dim_var, zero_one_dim_var_cpu)
 
-            self.assertEqual(zero_one_dim_var, zero_one_dim_var_cpu)
+                    two_three_dim_var = torch.var(x, dim=[2, 3], keepdim=keepdim, unbiased=unbiased)
+                    two_three_dim_var_cpu = torch.var(cpu_x, dim=[2, 3], keepdim=keepdim, unbiased=unbiased)
 
-            zero_one_dim_var_keepdim = torch.var(x, dim=[0, 1], keepdim=True, unbiased=False)
-            zero_one_dim_var_cpu_keepdim = torch.var(cpu_x, dim=[0, 1], keepdim=True, unbiased=False)
+                    self.assertEqual(two_three_dim_var, two_three_dim_var_cpu)
 
-            self.assertEqual(zero_one_dim_var_keepdim, zero_one_dim_var_cpu_keepdim)
-
-            two_three_dim_var = torch.var(x, dim=[2, 3], unbiased=False)
-            two_three_dim_var_cpu = torch.var(cpu_x, dim=[2, 3], unbiased=False)
-
-            self.assertEqual(two_three_dim_var, two_three_dim_var_cpu)
-
-            two_three_keepdim_var = torch.var(x, dim=[2, 3], keepdim=True, unbiased=False)
-            two_three_dim_keepvar_cpu = torch.var(cpu_x, dim=[2, 3], keepdim=True, unbiased=False)
-
-            self.assertEqual(two_three_keepdim_var, two_three_dim_keepvar_cpu)
-
-            all_var = torch.var(x, unbiased=True)
-            all_var_cpu = torch.var(cpu_x, unbiased=True)
-
-            self.assertEqual(all_var, all_var_cpu)
-
-            nil_dim_var = torch.var(x, dim=[], unbiased=True)
-            nil_dim_var_cpu = torch.var(cpu_x, dim=[], unbiased=True)
-
-            self.assertEqual(nil_dim_var, nil_dim_var_cpu)
-
-            nil_dim_var_keepdim = torch.var(x, dim=[], keepdim=True, unbiased=True)
-            nil_dim_var_cpu_keepdim = torch.var(cpu_x, dim=[], keepdim=True, unbiased=True)
-
-            self.assertEqual(nil_dim_var_keepdim, nil_dim_var_cpu_keepdim)
-
-            zero_dim_var = torch.var(x, dim=[0], unbiased=True)
-            zero_dim_var_cpu = torch.var(cpu_x, dim=[0], unbiased=True)
-
-            self.assertEqual(zero_dim_var, zero_dim_var_cpu)
-
-            zero_dim_var_keepdim = torch.var(x, dim=[0], keepdim=True, unbiased=True)
-            zero_dim_var_cpu_keepdim = torch.var(cpu_x, dim=[0], keepdim=True, unbiased=True)
-
-            self.assertEqual(zero_dim_var_keepdim, zero_dim_var_cpu_keepdim)
-
-            zero_one_dim_var = torch.var(x, dim=[0, 1], unbiased=True)
-            zero_one_dim_var_cpu = torch.var(cpu_x, dim=[0, 1], unbiased=True)
-
-            self.assertEqual(zero_one_dim_var, zero_one_dim_var_cpu)
-
-            zero_one_dim_var_keepdim = torch.var(x, dim=[0, 1], keepdim=True, unbiased=True)
-            zero_one_dim_var_cpu_keepdim = torch.var(cpu_x, dim=[0, 1], keepdim=True, unbiased=True)
-
-            self.assertEqual(zero_one_dim_var_keepdim, zero_one_dim_var_cpu_keepdim)
-
-            two_three_dim_var = torch.var(x, dim=[2, 3], unbiased=True)
-            two_three_dim_var_cpu = torch.var(cpu_x, dim=[2, 3], unbiased=True)
-
-            self.assertEqual(two_three_dim_var, two_three_dim_var_cpu)
-
-            two_three_keepdim_var = torch.var(x, dim=[2, 3], keepdim=True, unbiased=True)
-            two_three_dim_keepvar_cpu = torch.var(cpu_x, dim=[2, 3], keepdim=True, unbiased=True)
-
-            self.assertEqual(two_three_keepdim_var, two_three_dim_keepvar_cpu)
-
-        helper((4, 5, 6, 7))
-        # verify if a change in shape of input would cause problems with graph caching
-        helper((9, 5, 6, 7))
+        helper()
 
     # Test forward amax
     def test_amax(self):